Accurate and complete data is critical for effective health interventions and equitable care delivery. However, today’s public health organizations and Medicare agencies face significant challenges in matching and managing identity data across fragmented systems — in other words, in knowing who is who across their many programs and applications.
During a recent webinar, the Virginia Office of Data Governance and Analytics (ODGA) shared the challenges of establishing accurate identity data management and how they overcame them. Below are some valuable highlights from that discussion, but check out the webinar for a detailed account!
The power of identity data management in public health
Building a complete and trusted view of individuals is complex. For public health agencies, fragmented data across multiple systems often creates identity-matching challenges. Consider the following scenarios:
- Scenario 1: Jane Jefferson recently moved to a new address and changed her name from Jane Jones after she got married. Her records are scattered across three accounts, each holding a different medical history. The public health application must determine if these records belong to the same person to ensure accurate treatment and care.
- Scenario 2: Robert Smith’s data appears across various public health records, with discrepancies in his address, phone number, and last name spelling. The system must identify and consolidate these records to maintain a unified and accurate health profile, essential for emergency response and ongoing care.
- Scenario 3: Maria Lopez recently changed her name after adopting her child and relocated to a different city. Her immunization records are spread across different public health departments, risking gaps in vaccination tracking. The system must accurately match her records to prevent missed vaccinations and ensure comprehensive care.
These challenges are compounded by the need to incorporate social determinants of health (SDOH) data and indicators to comprehensively understand the populations they serve. This issue is particularly acute in public health, where understanding the whole person—not just their medical history but also their socio-economic context—is essential for delivering effective care and achieving health equity.
Leveraging identity solutions to drive health equity
Accurate identity data management — through master person index (MPI) and master data management (MDM) technologies — has a transformative impact on public health initiatives. The ability to link records across systems and natively incorporate enrichment SDOH data enables public health agencies to address disparities and improve health outcomes.
A key benefit of accurate identity data management is creating a holistic and longitudinal view of individuals within the public health system. This requires linking records from various intra-departmental and inter-departmental data sources, ensuring all relevant information about an individual is connected, regardless of when or where it was recorded.
The ODGA’s identity data management solution helped create a holistic and longitudinal view of its populations, accurately linking records across its intra-department and inter-department data sources. By assigning a unique identifier to each individual and natively integrating SDOH data as part of that identification process, the ODGA has improved its record-matching accuracy significantly as well as built a more comprehensive view of each person’s socioeconomic factors.
This comprehensive view is crucial for understanding the broader health landscape and addressing health disparities and gaps in care. It pinpoints areas where specific populations may be at higher risk for poor health outcomes, enabling targeted interventions, such as allocating resources to underserved communities or designing programs tailored to vulnerable populations’ needs.
And accurate identity data management improves individual health outcomes and supports broader public health goals like epidemic tracking and disease prevention. By ensuring that all relevant data is accurately linked and easily accessible, public health agencies can respond more quickly and effectively to emerging health threats. This capability is particularly vital when rapid intervention is necessary to prevent disease spread or manage public health crises.
Improving health equity through SDOH data integration
SDOH encompasses various factors, such as income, ethnicity, race, education, occupation, and living conditions, which can significantly influence health outcomes. By integrating this data, public health agencies can better understand the underlying causes of health inequities and tailor interventions to address these gaps more effectively.
Public health agencies must append comprehensive enrichment data to individual records, including detailed SDOH attributes. This offers a more complete picture of an individual’s health context. For instance, understanding a person’s income level or housing stability can illuminate barriers to accessing healthcare, allowing public health organizations to design targeted interventions that improve health outcomes for vulnerable populations.
SDOH data integration is particularly relevant in the context of Medicare, where disparities in access to care and health outcomes are often pronounced. By leveraging SDOH data, Medicare programs can better identify at-risk populations, ensure resources are allocated equitably, and track the effectiveness of interventions to reduce health disparities. Recognizing that individuals in lower-income brackets may face transportation challenges can lead to initiatives like mobile health clinics or telehealth services, improving access to care.
Let’s look at these two examples: Sofia is a 34-year-old woman and Isabella is 32; from their Medicaid enrollment records we know they live in the same area, but that’s all we know. By pulling in enrichment data for indicators like socioeconomic factors, race/ethnicity, and interests and affinities, we can learn much more about the social determinants of health for these two members.
- Isabella has 3 kids and lives with her partner and another adult, her mom, in a house that they own, has access to two cars, and she speaks English and Spanish.
- Sofia also has three kids but is a single parent with no other adult in her household, she rents an apartment, does not own a car, and only speaks Spanish.
Knowing these things, public health agencies can tailor services, communication, and other interactions to help Sofia get her children to doctor’s appointments or access other supportive services. This ensures a smoother journey, seamless access to care, and better outcomes.
Effective public health initiatives depend on seamless data sharing across departments and external partners. They need secure and accurate information sharing to unlock new insights from other systems and partners. This capability is essential for comprehensive public health analytics, allowing for a more coordinated and informed approach to improving overall population health. And it fosters cross-agency collaboration, often cited as one of the most challenging aspects of public health management.
The ODGA has successfully leveraged similar capabilities to enhance its data-driven initiatives. By integrating SDOH data into its systems, the ODGA has gained a more nuanced understanding of the social factors affecting health outcomes in the state, enabling more targeted and effective public health interventions.
Ultimately, the ODGA recognizes that integrating SDOH data is not just a technical enhancement; it is a transformative approach that allows public health and Medicare systems to address the root causes of health inequities, ensuring that all individuals have the opportunity to achieve their best possible health.
The road ahead: Advancing public health with Verato
Investing in robust identity management solutions is no longer optional for public health and Medicare agencies. As these organizations continue to face increasing demands for data accuracy and interoperability, the ability to build a complete and trusted view of the populations they serve will be critical. Public health agencies seek to enhance their efforts to achieve health equity, improve care coordination, and ultimately deliver better health outcomes—and Verato offers best-in-class solutions with our patented referential matching approach that identifies who is who in every context with independently verified and industry-leading accuracy, and enriches that view with SDOH indicators that are essential for delivering better outcomes.
To learn more about how Verato’s identity management solutions can transform public health initiatives, watch our webinar with ODGA of Virginia and reach out for a demo!
